Comprehensive side-by-side LLM comparison
Gemini 2.0 Flash leads with 38.0% higher average benchmark score. Gemini 2.0 Flash offers 800.8K more tokens in context window than DeepSeek R1 Distill Qwen 32B. Both models have similar pricing. Gemini 2.0 Flash supports multimodal inputs. Overall, Gemini 2.0 Flash is the stronger choice for coding tasks.
DeepSeek
DeepSeek R1 Distill Qwen 32B is a language model developed by DeepSeek. It achieves strong performance with an average score of 74.2% across 4 benchmarks. It excels particularly in MATH-500 (94.3%), AIME 2024 (83.3%), GPQA (62.1%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek's latest advancement in AI technology.
Gemini 2.0 Flash is a multimodal language model developed by Google. It achieves strong performance with an average score of 66.7% across 13 benchmarks. It excels particularly in Natural2Code (92.9%), MATH (89.7%), FACTS Grounding (83.6%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents Google's latest advancement in AI technology.
1 month newer
Gemini 2.0 Flash
2024-12-01
DeepSeek R1 Distill Qwen 32B
DeepSeek
2025-01-20
Cost per million tokens (USD)
DeepSeek R1 Distill Qwen 32B
Gemini 2.0 Flash
Context window and performance specifications
Average performance across 15 common benchmarks
DeepSeek R1 Distill Qwen 32B
Gemini 2.0 Flash
Gemini 2.0 Flash
2024-08-01
Available providers and their performance metrics
DeepSeek R1 Distill Qwen 32B
DeepInfra
Gemini 2.0 Flash
DeepSeek R1 Distill Qwen 32B
Gemini 2.0 Flash
DeepSeek R1 Distill Qwen 32B
Gemini 2.0 Flash